Abstract [en]

Background: In order to satisfy different needs, medical terminology systems musthave richer structures. This study examines whether a Swedish primary health careversion of the mono-hierarchical ICD-10 (KSH97-P) may obtain a richer structureusing category and chapter mappings from KSH97-P to SNOMED CT and SNOMEDCT’s structure. Manually-built mappings from KSH97-P’s categories and chapters toSNOMED CT’s concepts are used as a starting point

Results: The mappings are manually evaluated using computer-producedinformation and a small number of mappings are updated. A new and polyhierarchicalchapter division of KSH97-P’s categories has been created using thecategory and chapter mappings and SNOMED CT’s generic structure. In the newchapter division, most categories are included in their original chapters. Aconsiderable number of concepts are included in other chapters than their originalchapters. Most of these inclusions can be explained by ICD-10’s design. KSH97-P’scategories are also extended with attributes using the category mappings andSNOMED CT’s defining attribute relationships. About three-fourths of all conceptsreceive an attribute of type Finding site and about half of all concepts receive anattribute of type Associated morphology. Other types of attributes are less common.

Conclusions: It is possible to use mappings from KSH97-P to SNOMED CT andSNOMED CT’s structure to enrich KSH97-P’s mono-hierarchical structure with a polyhierarchicalchapter division and attributes of type Finding site and Associatedmorphology. The final mappings are available as additional files for this paper.

Abstract [en]

Methods for presentation of disease and health problem distribution in a health care environment rely among other things on the inherent structure of the controlled terminology used for coding. In the present study, this aspect is explored with a focus on ICD-10 and SNOMED CT. The distribution of 2,5 million diagnostic codes from primary health care in the Stockholm region is presented and analyzed through the “lenses” of ICD-10 and SNOMED CT. The patient encounters, originally coded with a reduced set of ICD-10 codes used in primary health care in Sweden, were mapped to SNOMED CT concepts through a mapping table. The method used for utilizing the richer structure of SNOMED CT as compared to ICD-10 is presented, together with examples of produced disease distributions. Implications of the proposed method for enriching a traditional classification such as ICD-10 through mappings to SNOMED CT are discussed.

Abstract [en]

Background: Exchange of Electronic Health Record (EHR) data between systems from different suppliers is a major challenge. EHR communication based on archetype methodology has been developed by openEHR and CEN/ISO. The experience of using archetypes in deployed EHR systems is quite limited today. Currently deployed EHR systems with large user bases have their own proprietary way of representing clinical content using various models. This study was designed to investigate the feasibility of representing EHR content models from a regional EHR system as openEHR archetypes and inversely to convert archetypes to the proprietary format. Methods: The openEHR EHR Reference Model (RM) and Archetype Model (AM) specifications were used. The template model of the Cambio COSMIC, a regional EHR product from Sweden, was analyzed and compared to the openEHR RM and AM. This study was focused on the convertibility of the EHR semantic models. A semantic mapping between the openEHR RM/AM and the COSMIC template model was produced and used as the basis for developing prototype software that performs automated bidirectional conversion between openEHR archetypes and COSMIC templates. Results: Automated bi-directional conversion between openEHR archetype format and COSMIC template format has been achieved. Several archetypes from the openEHR Clinical Knowledge Repository have been imported into COSMIC, preserving most of the structural and terminology related constraints. COSMIC templates from a large regional installation were successfully converted into the openEHR archetype format. The conversion from the COSMIC templates into archetype format preserves nearly all structural and semantic definitions of the original content models. A strategy of gradually adding archetype support to legacy EHR systems was formulated in order to allow sharing of clinical content models defined using different formats. Conclusion: The openEHR RM and AM are expressive enough to represent the existing clinical content models from the template based EHR system tested and legacy content models can automatically be converted to archetype format for sharing of knowledge. With some limitations, internationally available archetypes could be converted to the legacy EHR models. Archetype support can be added to legacy EHR systems in an incremental way allowing a migration path to interoperability based on standards.

Abstract [sv]

Lexicography is a realm of growing academic specialization. Dictionaries map meaning onto use. We have innumerable dictionaries on different subjects and for different purposes which we keep referring to, time and again. Despite the frequency with which dictionaries are unquestioningly consulted, many have little idea of what actually goes into making them or how meanings are definitively ascertained. We have become so accustomed to using dictionaries that we fail to take notice of the effort and time spent in their making. Understanding the finer nuances of the art of dictionary-making will be of interest to everyone. With changing times and the penetration of technology, the bulkier forms of dictionaries have given way to softer forms. This book updates the reader to the changing notions of the lexicon and dictionary-making in the new realm of modern technology and newer electronic tools. The book introduces us to lexicography and leads us to dictionaries for general and specific purposes. It examines dictionary compilation and research and enables compilers, users, educators and publishers to look anew at the art of lexicography. It duly takes into account the fact that dictionaries are meant to fulfill the needs of specific user groups and reflects the same in the chapters devoted to various professional dictionaries, which have recently achieved widespread recognition in the lexicographical literature. A good read for students of linguistics, teachers and translators apart from general readers interested in knowing the intricate art of making a dictionary.

Place, publisher, year, edition, pages

Hyderabad, India: The Icfai University Press, 2009 Edition: 1

National Category

General Language Studies and Linguistics Computer and Information Sciences

Abstract [en]

Computerized guidelines can provide decision support and facilitate the use of clinical guidelines. Several computerized guideline representation models (GRMs) exist but the poor interoperability between the guideline systems and the Electronic Health Record (EHR) systems limits their clinical usefulness. In this study we analyzed the clinical use of a published lymphoma chemotherapy guideline. We found that existing GRMs have limitations that can make it difficult to meet the clinical requirements. We hypothesized that guidelines could be represented as data and logic using openEHR archetypes, templates and rules. The design was tested by implementing the lymphoma guideline. We conclude that using the openEHR models and rules to represent chemotherapy guidelines is feasible and confers several advantages both from a clinical and from an informatics perspective.

Abstract [en]

With the introduction of EHR two-level modelling and archetype methodologies pioneered by openEHR and standardized by CEN/ISO, we are one step closer to semantic interoperability and future-proof adaptive healthcare information systems. Along with the opportunities, there are also challenges. Archetypes provide the full semantics of EHR data explicitly to surrounding systems in a platform-independent way, yet it is up to the receiving system to interpret the semantics and process the data accordingly. In this paper we propose a design of an archetype-based platform-independent testing framework for validating implementations of the openEHR archetype formalism as a means of improving quality and interoperability of EHRs.

Abstract [en]

Background

The Archetype formalism and the associated Archetype Definition Language have been proposed as an ISO standard for specifying models of components of electronic healthcare records as a means of achieving interoperability between clinical systems. This paper presents an archetype editor with support for manual or semi-automatic creation of bindings between archetypes and terminology systems.

Methods

Lexical and semantic methods are applied in order to obtain automatic mapping suggestions. Information visualisation methods are also used to assist the user in exploration and selection of mappings.

Results

An integrated tool for archetype authoring, semi-automatic SNOMED CT terminology binding assistance and terminology visualization was created and released as open source.

Conclusion

Finding the right terms to bind is a difficult task but the effort to achieve terminology bindings may be reduced with the help of the described approach. The methods and tools presented are general, but here only bindings between SNOMED CT and archetypes based on the openEHR reference model are presented in detail.

Background

The Archetype formalism and the associated Archetype Definition Language have been proposed as an ISO standard for specifying models of components of electronic healthcare records as a means of achieving interoperability between clinical systems. This paper presents an archetype editor with support for manual or semi-automatic creation of bindings between archetypes and terminology systems.

Methods

Lexical and semantic methods are applied in order to obtain automatic mapping suggestions. Information visualisation methods are also used to assist the user in exploration and selection of mappings.

Results

An integrated tool for archetype authoring, semi-automatic SNOMED CT terminology binding assistance and terminology visualization was created and released as open source.

Conclusion

Finding the right terms to bind is a difficult task but the effort to achieve terminology bindings may be reduced with the help of the described approach. The methods and tools presented are general, but here only bindings between SNOMED CT and archetypes based on the openEHR reference model are presented in detail.